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PROPRIETARY DAHER SOCATA 21/03/20141 MASTER DEGREE DISSERTATION IN MECHANICAL, AERONAUTICAL ENGINEERING Development of an automatic shape optimization.

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Presentation on theme: "PROPRIETARY DAHER SOCATA 21/03/20141 MASTER DEGREE DISSERTATION IN MECHANICAL, AERONAUTICAL ENGINEERING Development of an automatic shape optimization."— Presentation transcript:

1 PROPRIETARY DAHER SOCATA 21/03/20141 MASTER DEGREE DISSERTATION IN MECHANICAL, AERONAUTICAL ENGINEERING Development of an automatic shape optimization platform for a laminar profile March - September 2013 Relatori : Prof. Jan Pralits Ing. Thomas Michon Studente : Marcello Tobia Benvenuto

2 PROPRIETARY DAHER SOCATA 2 Daher Socata produces the world’s fastest single turboprop aircraft: TBM 850. As each aeronautic company, Reduce the consumption it works every day to improve the aircraft performance. Increase the max. speed Fluid mechanics Reduce the drag on the surfaces: WING Introduction 21/03/2014

3 PROPRIETARY DAHER SOCATA 3 When a body is in motion in a flow, the flow adhere to it because of the viscosity. A thin layer arises close to the shape, called boundary layer. Physical phenomenon 21/03/2014

4 PROPRIETARY DAHER SOCATA 4 External disturbances can enter the boundary layer and generate a turbulent flow through a Transition process. Laminar boundary layer: Thin with regular streamlines; low skin friction. Turbulent boundary layer: Thick with irregular fluctuations; high skin friction. The transition phenomenon is very sensitive to the shape variations Physical phenomenon Skin Friction X/C 21/03/2014

5 PROPRIETARY DAHER SOCATA 5 Reduce the friction drag on an airfoil by keeping the flow laminar over the largest possible portion of the surface. Automatic Shape Optimization Advantages: 1) Save time during a process 2) Run multiple repetitive simulations 3) Analyze automatically the good results, finding the optimum Objective 21/03/2014

6 PROPRIETARY DAHER SOCATA 6 Optimization platform for 2D Geometry 2D optimization High and High/Low speed - results - discussion Creation wing - results - discussion Conclusions Future works Contents 21/03/2014

7 PROPRIETARY DAHER SOCATA 7 The wing’s behaviors are given by its profiles. Relative Thickness: 16% Chord: m Why a 2D geometry? 21/03/2014

8 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 8 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

9 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 9 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

10 PROPRIETARY DAHER SOCATA To limit the number of the geometric design variables 10 Describing the shape with a small set of inputs 9 Polynomial approximations of curvesCAD Software: Catia V 5 Create the 2D geometry 21/03/2014

11 PROPRIETARY DAHER SOCATA 11 Design Parameters Constraints Radius of the circle Position of point 2 and 9 inside square Thickness of trailing edge Tension of points 2,3,8,9 Chord = 1 meter Thickness at 25% and 75% of the chord fixed. Create the 2D geometry 21/03/2014

12 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 12 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

13 PROPRIETARY DAHER SOCATA 13 O-type domain Radius = 90 meters Different domains and meshes have been investigated to find the best grid in terms of time and quality Grid close to the profile: Profile Grid Create the domain and the mesh 21/03/2014

14 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 14 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

15 PROPRIETARY DAHER SOCATA 15 Numerical solution of the Navier-Stokes’s equations Velocity and pressure distribution FLUENT Pressure Coefficient distribution on the root airfoil of TBM 850. Cruise conditions. Key point for the stability analysis Smoothness Good quality Flow solver X/C Cp 21/03/2014

16 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 16 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

17 PROPRIETARY DAHER SOCATA 17 bl3D code It calculates the parameters of the boundary layer from the Cp distribution Laminar Boundary Layer's Equations Boundary layer and its stability: bl3D 21/03/2014

18 PROPRIETARY DAHER SOCATA 18 NOLOT is based on the Linear Stability: Flow decomposed in mean flow and unsteady disturbances u = U + u' The unsteady disturbance is represented by a wave with infinitesimal amplitude Boundary layer and its stability: NOLOT Streamwise Wave number Spanmwise Wave number Frequency 21/03/2014

19 PROPRIETARY DAHER SOCATA 19 Semi-empirical e N method Mack’s Law: N = – 2.4 ln(Ti) < Ti < N factor Turbulence intensity Boundary layer and its stability: NOLOT 21/03/2014

20 PROPRIETARY DAHER SOCATA 20 1.To maximize the position of transition 1.To minimize ∆Cl = |Cl – Cl TBM | 1.To minimize ∆Cm = |Cm – Cm TBM | A change of the shape of a profile can lead to different value of Cl and Cm Changes of global repartition of lift Stability problems Stalling problems Objective functions 21/03/2014

21 PROPRIETARY DAHER SOCATA Create the 2D geometry Create the domain and the mesh Flow Solver Boundary layer and its stability 21 Catia V 5 ANSYS: Design Modeler and Mesh ANSYS : Fluent bl3D and Nolot code Optimization platform Mode Frontier Optimization steps and tools 21/03/2014

22 PROPRIETARY DAHER SOCATA 22 Optimization platform: Mode Frontier 21/03/2014

23 PROPRIETARY DAHER SOCATA 23 Lift and Mom. coeff ∆Cl ∆Cm Optimization platform: Mode Frontier 21/03/2014

24 PROPRIETARY DAHER SOCATA 24 Optimization platform for 2D Geometry 2D optimization High and High/Low speed - results - discussion Creation wing - results - discussion Conclusions Future works Contents 21/03/2014

25 PROPRIETARY DAHER SOCATA 25 high speed (cruise): M=0.51; h=26000 feet; aoa=0 degrees Strategy optimization - explore all the domain of input parameters DOE - optimize the best profiles found by DOE with genetic algorithm Optimization 2D High speed 21/03/2014

26 PROPRIETARY DAHER SOCATA profiles have been explored in 8 days Transition location ∆Cl Max ∆Cl 3% TBM (trans. 26% of the chord) Max trans. 47% of the chord Pareto front opt. 2D high speed 21/03/2014

27 PROPRIETARY DAHER SOCATA 27 Best solution opt. 2D high speed BLACK = TBMRED = BEST 21/03/2014

28 PROPRIETARY DAHER SOCATA 28 Solution not robust 0.07% of 1765 mm = 1.19 mm c A big influence of the leading edge on the transition Robustness solution for manufacturing? 21/03/2014

29 PROPRIETARY DAHER SOCATA 29 To evaluate the difference of drag, the SST-transition model is used in Fluent to study the natural transition: Drag evaluation with transition model 21/03/2014

30 PROPRIETARY DAHER SOCATA 30 - High speed (cruise): M=0.51; h=26000 feet; aoa=0 degrees - Low speed (take-off): M=0.18; h=0; aoa= > 15 degrees To analyze stall characteristics at low speed, the profile has been optimized also at take-off conditions Optimization 2D High/Low speed 21/03/2014

31 PROPRIETARY DAHER SOCATA 31 Cruise condition: 1.To maximize the transition location 2.To minimize ∆Cl and ∆Cm Take-off condition: 1.Maximize the max Lift coefficient Objective functions 21/03/2014

32 PROPRIETARY DAHER SOCATA 32 Pareto front Transition high speed Cl low speed The objective functions are in opposition one with the other The same optimization has been done for the tip profile of the wing Pareto front 2D opt. High/low speed 21/03/2014

33 PROPRIETARY DAHER SOCATA 33 High speed Big sensibility of the phenomenon by the shape variations Transition moved from 26% to 47% of the chord Viscous drag reduced of 14.26% Improvements limited by the constraints of the shape: transition occurs close to the maximum thickness High/low speed Each flight condition requires a different optimal shape The presence of a new O.F. has not penalized the transition (42%) Improvements limited by the constraints of the shape Discussion optimization 2D 21/03/2014

34 PROPRIETARY DAHER SOCATA 34 Optimization platform for 2D Geometry 2D optimization High and High/Low speed - results - discussion Creation wing - results - discussion Conclusions Future works Contents 21/03/2014

35 PROPRIETARY DAHER SOCATA 35 Creation of a wing with the optimal root and tip profile obtained previously Wing parameters: The same of the wing of TBM span: mm - dihedral: 6.5 degree Creation wing 21/03/2014

36 PROPRIETARY DAHER SOCATA 36 To compare the wing of the TBM 850 with the wing using the optimal profiles. Skin Friction TBM NEW CFD Simulation 3D 21/03/2014

37 PROPRIETARY DAHER SOCATA 37 WingVisc. dragPress. dragTotal dragLift coeff TBM New Skin friction on profile at 50% of the span Results 3D Skin Friction Chord New TBM 21/03/2014

38 PROPRIETARY DAHER SOCATA 38 The validation on the wing has given unexpected results in terms of drag: The effects of the flows on 2D and 3D geometry are different - trailing vortex - cross flow disturbances X - Wall shear stress Discussion 21/03/2014

39 PROPRIETARY DAHER SOCATA 39 The validation on the wing has given unexpected results in terms of drag: The effects of the flows on 2D and 3D geometry are different - trailing vortex - cross flow disturbances Discussion 21/03/2014

40 PROPRIETARY DAHER SOCATA 40 Optimization platform for 2D Geometry 2D optimization High and High/Low speed - results - discussion Creation wing - results - discussion Conclusions Future works Contents 21/03/2014

41 PROPRIETARY DAHER SOCATA 41 I am familiar with software like Catia V 5, Fluent (2D and 3D), Fortran, Python, modeFRONTIER I created an automatic shape optimization for 2D geometry The strategy used, has allowed to obtain good results for 2D geometry - transition phenomenon delayed from 26% to 47% of the chord - Viscous drag reduced more than 14% Conclusions 21/03/2014

42 PROPRIETARY DAHER SOCATA 42 Optimization 2D: 1. New parameterization (CST) with other constraints can be tested 2. More time for the iterations can lead a better results 3D Validation: 1. To consider 3D effects we can run the following loop: Study the flow around the wing Take Cp distribution of three profiles of the wing (root, middle, tip) Run optimization platform for the three profiles To rebuild the wing with the three new profiles and study the flow on the wing Future work and suggestions 21/03/2014

43 PROPRIETARY DAHER SOCATA 43 Thank you for your attention 21/03/2014


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